Pipeline circuit architecture to provide in-memory computation functionality

ABSTRACT

Techniques and mechanisms for performing in-memory computations with circuitry having a pipeline architecture. In an embodiment, various stages of a pipeline each include a respective input interface and a respective output interface, distinct from said input interface, to couple to different respective circuitry. These stages each further include a respective array of memory cells and circuitry to perform operations based on data stored by said array. A result of one such in-memory computation may be communicated from one pipeline stage to a respective next pipeline stage for use in further in-memory computations. Control circuitry, interconnect circuitry, configuration circuitry or other logic of the pipeline precludes operation of the pipeline as a monolithic, general-purpose memory device. In other embodiments, stages of the pipeline each provide a different respective layer of a neural network.

BACKGROUND 1. Technical Field

Embodiments of the invention generally relate to operation of a memorydevice and more particularly, but not exclusively, to circuit structuresfor implementing an in-memory computation.

2. Background Art

In modern image, speech, and pattern recognition operations, comparing,matching, multiplying and other processing of sample data is oftenrequired. Machine learning algorithms are used in various applicationssuch as embedded-sensor networks and computer vision. The operation ofpattern recognition can be used for classification in machine learning.Pattern recognition is also used for multimedia applications such asobject detection or speech recognition. Computation in patternrecognition is one type of repetitive process which has traditionallyrequired regular memory accesses, and as such, has consumed significantenergy.

BRIEF DESCRIPTION OF THE DRAWINGS

The various embodiments of the present invention are illustrated by wayof example, and not by way of limitation, in the figures of theaccompanying drawings and in which:

FIG. 1A is a functional block diagram illustrating elements of a systemincluding a pipeline circuit architecture according to an embodiment.

FIG. 1B is a functional block diagram illustrating elements of a memorydevice to perform an in-memory computation according to an embodiment.

FIG. 1C is a functional block diagram illustrating elements of anintegrated circuit including a pipeline circuit to perform in-memorycomputation according to an embodiment.

FIG. 2 is a flow diagram illustrating elements of a method forperforming an in-memory computation with a pipeline according to anembodiment.

FIG. 3 is a functional block diagram illustrating elements of a memorydevice to function as a pipeline stage according to an embodiment.

FIG. 4 is a hybrid functional block and circuit diagram illustratingelements of a memory device to perform an in-memory computationaccording to an embodiment.

FIG. 5 is a sequence diagram illustrating various states of a memoryarray during in-memory computations according to an embodiment.

FIG. 6 is a node diagram illustrating elements of a neural networkimplemented with in-memory computations by a pipeline circuitarchitecture according to an embodiment.

FIG. 7A is a block diagram illustrating both an exemplary in-orderpipeline and an exemplary register renaming, out-of-orderissue/execution pipeline according to embodiments of the invention.

FIG. 7B is a block diagram illustrating both an exemplary embodiment ofan in-order architecture core and an exemplary register renaming,out-of-order issue/execution architecture core to be included in aprocessor according to embodiments of the invention.

FIG. 8 is a block diagram of a processor that may have more than onecore, may have an integrated memory controller, and may have integratedgraphics according to embodiments of the invention.

FIGS. 9 through 11 are block diagrams of exemplary computerarchitectures.

DETAILED DESCRIPTION

Embodiments discussed herein variously provide techniques and mechanismsfor performing in-memory computations each at a different respectivestage of circuitry having a pipelined, multi-stage architecture. As usedherein in the context of “in-memory computing,” “in-memory computeoperation,” “in-memory data computation” and related phrases, the term“in-memory” refers to the characteristic of an action being performedlocally at a memory device which includes both a memory array andinterface logic by which the memory device is to couple (indirectly orindirectly) to some memory controller, processor or other external hostagent. In some embodiments, a given stage is a memory device whichincludes an array of memory cells (or “memory array”) and circuitry,coupled thereto, which is operable to detect a logic state based on oneor more bits currently stored by the array. Such circuitry performs oneor more data computations based on the logic state and, for example,provides a computation result as data to be stored back to the firstarray.

In some embodiments, a pipeline comprises an in-series arrangement ofstages, some or all of which variously provide respective in-memorycomputation functionality. Functionality of the pipeline is applicationspecific in one or more respects—e.g., at least insofar as the pipelinecomprises interconnect circuitry, control circuitry, configurationcircuitry and/or other circuit logic which precludes operation of thepipeline as a monolithic general-purpose memory device. By way ofillustration and not limitation, one or more pipeline stages may be“hidden” stages, wherein the memory array of a hidden stage isaccessible to a memory controller (or other host logic external to thepipeline) only via one or more other stages of the pipeline.Alternatively or in addition, circuitry of the pipeline might dedicatedifferent regions of a memory array in a given pipeline stage (and/orregions of memory arrays in different respective pipeline stages) tostoring different types of data. Alternatively or in addition, controlcircuitry of the pipeline might be configured to automatically performmultiple memory array accesses and/or other operations according to anyof one or more predefined sequences. Furthermore, stages of a pipelinemay additionally or alternatively be configured to communicate with oneanother automatically—e.g., independent of any explicit commands from amemory controller which specify said communication. By providing aspecialized pipeline to perform multiple in-memory computations each ata respective pipeline stage, some embodiments variously enable powerand/or time efficient calculations to provide functionality of a neuralnetwork (for example).

The technologies described herein may be implemented in one or moreelectronic devices. Non-limiting examples of electronic devices that mayutilize the technologies described herein include any kind of mobiledevice and/or stationary device, such as cameras, cell phones, computerterminals, desktop computers, electronic readers, facsimile machines,kiosks, laptop computers, netbook computers, notebook computers,internet devices, payment terminals, personal digital assistants, mediaplayers and/or recorders, servers (e.g., blade server, rack mountserver, combinations thereof, etc.), set-top boxes, smart phones, tabletpersonal computers, ultra-mobile personal computers, wired telephones,combinations thereof, and the like. More generally, the technologiesdescribed herein may be employed in any of a variety of electronicdevices including a pipelined arrangement of stages which variouslyprovide in-memory computation functionality.

In the following description, numerous details are discussed to providea more thorough explanation of the embodiments of the presentdisclosure. It will be apparent to one skilled in the art, however, thatembodiments of the present disclosure may be practiced without thesespecific details. In other instances, well-known structures and devicesare shown in block diagram form, rather than in detail, in order toavoid obscuring embodiments of the present disclosure.

Note that in the corresponding drawings of the embodiments, signals arerepresented with lines. Some lines may be thicker, to indicate a greaternumber of constituent signal paths, and/or have arrows at one or moreends, to indicate a direction of information flow. Such indications arenot intended to be limiting. Rather, the lines are used in connectionwith one or more exemplary embodiments to facilitate easierunderstanding of a circuit or a logical unit. Any represented signal, asdictated by design needs or preferences, may actually comprise one ormore signals that may travel in either direction and may be implementedwith any suitable type of signal scheme.

Throughout the specification, and in the claims, the term “connected”means a direct connection, such as electrical, mechanical, or magneticconnection between the things that are connected, without anyintermediary devices. The term “coupled” means a direct or indirectconnection, such as a direct electrical, mechanical, or magneticconnection between the things that are connected or an indirectconnection, through one or more passive or active intermediary devices.The term “circuit” or “module” may refer to one or more passive and/oractive components that are arranged to cooperate with one another toprovide a desired function. The term “signal” may refer to at least onecurrent signal, voltage signal, magnetic signal, or data/clock signal.The meaning of “a,” “an,” and “the” include plural references. Themeaning of “in” includes “in” and “on.”

The term “device” may generally refer to an apparatus according to thecontext of the usage of that term. For example, a device may refer to astack of layers or structures, a single structure or layer, a connectionof various structures having active and/or passive elements, etc.Generally, a device is a three-dimensional structure with a plane alongthe x-y direction and a height along the z direction of an x-y-zCartesian coordinate system. The plane of the device may also be theplane of an apparatus which comprises the device.

The term “scaling” generally refers to converting a design (schematicand layout) from one process technology to another process technologyand subsequently being reduced in layout area. The term “scaling”generally also refers to downsizing layout and devices within the sametechnology node. The term “scaling” may also refer to adjusting (e.g.,slowing down or speeding up—i.e. scaling down, or scaling uprespectively) of a signal frequency relative to another parameter, forexample, power supply level.

The terms “substantially,” “close,” “approximately,” “near,” and“about,” generally refer to being within +/−10% of a target value. Forexample, unless otherwise specified in the explicit context of theiruse, the terms “substantially equal,” “about equal” and “approximatelyequal” mean that there is no more than incidental variation betweenamong things so described. In the art, such variation is typically nomore than +/−10% of a predetermined target value.

It is to be understood that the terms so used are interchangeable underappropriate circumstances such that the embodiments of the inventiondescribed herein are, for example, capable of operation in otherorientations than those illustrated or otherwise described herein.

Unless otherwise specified the use of the ordinal adjectives “first,”“second,” and “third,” etc., to describe a common object, merelyindicate that different instances of like objects are being referred toand are not intended to imply that the objects so described must be in agiven sequence, either temporally, spatially, in ranking or in any othermanner.

For the purposes of the present disclosure, phrases “A and/or B” and “Aor B” mean (A), (B), or (A and B). For the purposes of the presentdisclosure, the phrase “A, B, and/or C” means (A), (B), (C), (A and B),(A and C), (B and C), or (A, B and C).

The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,”“under,” and the like in the description and in the claims, if any, areused for descriptive purposes and not necessarily for describingpermanent relative positions. For example, the terms “over,” “under,”“front side,” “back side,” “top,” “bottom,” “over,” “under,” and “on” asused herein refer to a relative position of one component, structure, ormaterial with respect to other referenced components, structures ormaterials within a device, where such physical relationships arenoteworthy. These terms are employed herein for descriptive purposesonly and predominantly within the context of a device z-axis andtherefore may be relative to an orientation of a device. Hence, a firstmaterial “over” a second material in the context of a figure providedherein may also be “under” the second material if the device is orientedupside-down relative to the context of the figure provided. In thecontext of materials, one material disposed over or under another may bedirectly in contact or may have one or more intervening materials.Moreover, one material disposed between two materials may be directly incontact with the two layers or may have one or more intervening layers.In contrast, a first material “on” a second material is in directcontact with that second material. Similar distinctions are to be madein the context of component assemblies.

The term “between” may be employed in the context of the z-axis, x-axisor y-axis of a device. A material that is between two other materialsmay be in contact with one or both of those materials, or it may beseparated from both of the other two materials by one or moreintervening materials. A material “between” two other materials maytherefore be in contact with either of the other two materials, or itmay be coupled to the other two materials through an interveningmaterial. A device that is between two other devices may be directlyconnected to one or both of those devices, or it may be separated fromboth of the other two devices by one or more intervening devices.

As used throughout this description, and in the claims, a list of itemsjoined by the term “at least one of” or “one or more of” can mean anycombination of the listed terms. For example, the phrase “at least oneof A, B or C” can mean A; B; C; A and B; A and C; B and C; or A, B andC. It is pointed out that those elements of a figure having the samereference numbers (or names) as the elements of any other figure canoperate or function in any manner similar to that described, but are notlimited to such.

In addition, the various elements of combinatorial logic and sequentiallogic discussed in the present disclosure may pertain both to physicalstructures (such as AND gates, OR gates, or XOR gates), or tosynthesized or otherwise optimized collections of devices implementingthe logical structures that are Boolean equivalents of the logic underdiscussion.

In addition, the various elements of combinatorial logic and sequentiallogic discussed in the present disclosure may pertain both to physicalstructures (such as AND gates, OR gates, or XOR gates), or tosynthesized or otherwise optimized collections of devices implementingthe logical structures that are Boolean equivalents of the logic underdiscussion.

It is pointed out that those elements of the figures having the samereference numbers (or names) as the elements of any other figure canoperate or function in any manner similar to that described, but are notlimited to such.

FIG. 1A shows features of a system 100 to perform in-memory computeoperations according to an embodiment. System 100 is one example of anembodiment wherein circuitry provides a pipeline architecture, two ormore stages of which each include a respective memory array andcircuitry, coupled thereto, to perform in-memory computation based ondata which is stored at said memory array. Such stages are coupled toone another in an in-series pipeline configuration which, for example,enables functionality of a neural network.

As shown in FIG. 1A, system 100 includes a pipeline 110 and sourceand/or sink circuitry SS 120, coupled thereto, to operate as a source ofdata provided to pipeline 110, or as a sink to receive data frompipeline 110. SS 120 comprises circuitry to control operation ofpipeline 110—e.g., where SS 120 includes some or all circuitry of amulti-core (or single core) processor, such as one including theillustrative core circuitry 122 shown. Core circuitry 122 comprises anyof a variety of suitable circuit blocks that, for example, are adaptedfrom conventional processor core architectures. Examples of such circuitblocks include, but are not limited to, an arithmetic-logic unit (ALU),register file, scheduler, instruction fetch, instruction decoder, branchprediction unit, instruction translation lookaside buffer (TLB),instruction cache memory, data cache memory, and/or the like.

In the example shown, SS 120 further comprises memory interfacecircuitry 124 to provide access to pipeline 110 for core circuitry 122.A core comprising core circuitry 122 is configured to execute ageneral-purpose operating system and/or other software for a computerplatform that includes system 100. Memory interface circuitry 124comprises interconnects and/or memory controller logic coupled tofacilitate access to pipeline 110 by core circuitry 122. For example, insome embodiments, one core of a processor comprises each of corecircuitry 122, memory interface circuitry 124 and pipeline 110—e.g.,wherein memory interface circuitry 124 also provides an interface to,and/or control of, one or more cache memories of the processor core.Alternatively, pipeline 110 may be distinct from any processor core ofSS 120 and, in some embodiments, distinct from any processor whichincludes SS 120. For example, in other embodiments, one core of aprocessor (the core comprising core circuitry 122) is coupled to memoryinterface circuitry 124—e.g., wherein memory interface circuitry 124 isan integrated memory controller of the processor. In still anotherembodiment, memory interface circuitry 124 and pipeline 110 are eachdistinct from, but communicatively coupled to, a processor whichcomprises core circuitry 122.

In one embodiment, pipeline 110 is circuitry of an integrated circuit(IC) die other than any IC die of SS 120. For example, pipeline 110 maybe a packaged device other than any packaged device of SS 120. Inanother embodiment, system 100 is a system-on-chip (SoC) device.Although some embodiments are not limited in this regard, system 100 mayfurther comprise or couple to one or more other resources (such as theillustrative repository 130 shown) which, for example, facilitaterelatively long-term data storage. By way of illustration and notlimitation, repository 130 includes a solid-state drive (SSD), hard diskdrive (HDD) or the like. Alternatively or in addition, memory resourcesof repository 130 may function as one or more memory caches which areincluded in (or coupled to) SS 120.

SS 120 is coupled to pipeline 110 via one or more interconnects, such asthe illustrative interconnects 126, 128 shown. Pipeline 110 comprises aplurality of stages (e.g., including the illustrative stages 112 a, 112b, . . . , 112 n) which are coupled to communicate each with arespective one or more other stages of pipeline 110. In an exampleembodiment, an in-series stage arrangement of pipeline 110 is providedwith interconnects—e.g., including the illustrative interconnects 118 a,118 b shown—which are variously coupled each between a respective two ofstages 112 a,112 b, . . . , 112 n. Some or all such stages each includea respective input interface and a respective output interface (e.g.,wherein stages 112 a, 112 b, . . . , 112 n include respective inputinterfaces 114 a, 114 b, . . . , 114 n and respective output interfaces116 a, 116 b, . . . , 116 n). An input interface of a given pipelinestage receives one or more data signals, command signals, controlsignals and/or other communication from one of SS 120 or a respectivepreceding pipeline stage. Similarly, an output interface of a givenpipeline stage provides data, command, control and/or other signalcommunications to one of SS 120 or a respective next pipeline stage.

In the example embodiment shown, interconnect 126 facilitatescommunication from memory interface circuitry 124 (or other logic of SS120) to input interface 114 a of stage 112 a—e.g., where interconnect128 facilitates communication from output interface 116 n of stage 112 nto memory interface circuitry 124. In other embodiments, pipeline 110alternatively comprises a consolidated input/output interface whichprovides functionality of both input interface 114 a and outputinterface 116 n—e.g., wherein a single bus and/or other signal linesprovide functionality of both interconnects 126, 128.

Interconnects 126, 128 comprise respective signal lines to variouslyexchange signaling between SS 120 and pipeline 110. In an exampleembodiment, one or each of interconnects 126, 128 include a data bus, anaddress bus, a command bus and/or any of a variety of combinations ofsome or all such buses in support of SS 120 accessing or otherwisecontrolling pipeline 110. Interconnect 126 may further include one ormore control signal lines for control signaling (e.g., other thancommand, address and/or data signaling) to pipeline 110. A reader ofskill in the art will appreciate that such control signal linescommunicate, for example, one or more of a chip select signal, a writeenable signal, an output enable signal, a clock signal, a column addressstrobe signal, a row address strobe signal or any of a variety of otherconventional control signals. One or more interconnects betweenrespective stages of pipeline 110 (e.g., one of interconnects 118 a, 118b) facilitate similar command, address, data, and/or controlcommunications. As discussed herein, one or more signals lines of agiven interconnect indicate (explicitly or implicitly) that one or morein-memory computations are to be performed each at a respective stage ofpipeline 110, based on data which is stored at a local array of memorycells.

In some embodiments, integrated circuitry of a processor (and in someembodiments, of an individual processor core) comprises both pipeline110 and SS 120. For example, interconnects 126, 128 are each furthercoupled to access one or more cache memories of SS 120—e.g., wherein acache memory and pipeline 110 are integrated in the same processor core,and where memory interface circuitry 124 provides both memory controllerfunctionality to operate pipeline 110 and cache controller functionalityto access the cache memory. In one such embodiment, respective memoryarrays of the cache memory of pipeline have the same type of memorycells (e.g., SRAM memory cells), the same sized rows and/or columns ofsuch memory cells, and/or the like.

In various embodiments, interconnect circuitry—e.g., including a portionof interconnect 126 and/or interconnect 128—is coupled between memoryinterface circuitry 124 and pipeline 110, and also coupled betweenmemory interface circuitry 124 and a cache memory. For example, memoryinterface circuitry 124 may use a shared bus to various communicatedifferent commands and/or data each with a respective one of pipeline110 and a cache memory of a processor which includes SS 120. In oneexample embodiment, such cache memory resides in a processor core whichincludes core circuitry 122, memory interface circuitry 124 and pipeline110. In another embodiment, the cache memory is distinct from, butcommunicatively coupled to, each processor core of a processor—e.g.,wherein the cache memory and pipeline 110 are available for sharedaccess by any such processor core.

FIG. 1C shows features of an integrated circuit (IC) 160 to performin-memory compute operations according to an embodiment. IC 160 hasfeatures of system 100 in some embodiments. As shown in FIG. 1C, IC 160comprises core circuitry 162, controller circuitry 164, an interconnect166, an interconnect 168, and a pipeline circuit 170 that—forexample—correspond functionally to core circuitry 122, controllercircuitry 124, interconnect 126, interconnect 128, and pipeline 110(respectively). IC 160 comprises some or all circuitry of aprocessor—e.g., wherein core circuitry 162 provides some or allfunctionality of one or more processor cores.

Controller circuitry 164 comprises logic which, by controlling operationof pipeline circuit 170, enables access by core circuitry 162 to memoryresources of pipeline circuit 170. In the example embodiment shown,pipeline circuit 170 and a cache memory 180 of IC 160 each compriserespective portions of such memory resources. Pipeline circuit 170includes an in-series arrangement of multiple stages (such as theillustrative stages 171-174 shown) which, for example, correspondfunctionally to stages 112 a, 112 b, . . . , 112 n.

Interconnect 166 is coupled to facilitate communication from controllercircuitry 164 to an input interface of stage 171, and interconnect 168is coupled to facilitate communication from an output interface of stage174 to controller circuitry 164. At least some signaling between variousrespective ones of stages 171-174—e.g., including data signaling and, insome embodiments, command/address signaling—takes place entirely withinpipeline circuit 170, and independent of any relaying of said signalingvia controller circuitry 164. In such an embodiment, at least someportion of interconnect 166 and interconnect 168 is also used to accesscache memory 180—e.g., wherein other portions of interconnect 166 andinterconnect 168 variously branch and couple to facilitate signalcommunication between controller circuitry 164 and one or more arrays181 (e.g., banks) of cache memory 180. Although interconnect 166, 168are shown as distinct paths for signaling from and to (respectively)controller circuitry 164, some embodiments alternatively comprise signallines coupled provide bi-directional signaling.

For some or all of stages 112 a, . . . 112 n, each such stage comprisesa respective memory array and circuitry, coupled thereto, which is toperform an in-memory computation based on data currently stored at saidmemory array. For example, FIG. 1B shows features of a memory device150, according to an embodiment, which is operable to function as astage of a pipeline—wherein circuitry of memory device 150 is variouslyconfigurable to facilitate operation in an in-series arrangement withone or more similar memory devices. In an embodiment, memory device 150provides functionality of one of stages 112 a, 112 b, . . . , 112 n, forexample. Certain features of stages 112 a, 112 b, . . . , 112 n aredescribed herein with reference to the illustrative memory device 150.It will be apparent, however, to one skilled in the art that some or allof stages 112 a, 112 b, . . . , 112 n may each have one or morerespective additional or alternative features.

In the example embodiment shown, memory device 150 comprises an inputinterface 151 (e.g., one of input interfaces 114 a, 114 b, . . . , 114n) to couple to a preceding pipeline stage or, alternatively, to aninterconnect such as interconnect 126. Memory device 150 furthercomprises an output interface 152 (e.g., one of output interfaces 116 a,116 b, . . . , 116 n) to couple to a next pipeline stage or,alternatively, to an interconnect such as interconnect 128. Based oncommunication received via input interface 151, access logic AL 153 ofmemory device 150 facilitates, at least in part, access to an array MA154 of memory cells (or “memory array”). Such access is provided forservicing one or more commands from SS 120 or, alternatively, from apreceding stage of a pipeline which includes memory device 150. Accesslogic AL 153 includes, or operate in conjunction with, logic of memorydevice 150 which provides memory resource access according toconventional techniques. In an embodiment, AL 153 includes or couples tocommand logic and address logic which is used to decode an accessinstruction to the proper memory location within MA 154. Command logicand address logic are implemented, for example, with a state machine orother such circuitry.

In an embodiment, array MA 154 includes any of a variety of types ofmemory technology wherein memory cells are arranged in rows andcolumns—e.g., where data stored by said cells is accessible via wordlines and bit lines, or an equivalent thereof. In one embodiment, MA 154includes static random-access memory (or “SRAM”). However, any ofvarious other types of memory cell technologies may be adapted foroperation to facilitate in-memory computation, as described herein. Inthe example embodiment shown, memory device 150 includes a memory arrayMA 154, which represents one or more logical and/or physical groups ofmemory. An example of one such grouping of memory is a bank of memoryresources that, for example, includes storage elements arranged in rowsand columns. In various embodiments, at least some data is stored inarray 154 in an arrangement wherein the bits of a given value are storedin different respective word lines, the bits each accessible via thesame bit line of the array (e.g., wherein the bits of the value arearranged along the bit line each according to their respective bitsignificance). Such an arrangement facilitates an in-memory computationwhich operates on bits of different values, where said bits have thesame bit significance.

During operation of system 100, SS 120 sends commands or instructions topipeline 110 over a bus of interconnect 126. Such commands areinterpreted by memory device 150 (or other such device configured toimplement stage 112 a)—e.g. including access logic AL 153 of memorydevice 150 decoding command information to perform a variety of accessfunctions within the memory and/or decoding address information withcolumn logic and/or row logic. In an embodiment, such logic accesses aspecific location in MA 154 with a combination of a column addressstrobe or signal (CAS) and a row address strobe or signal (RAS). Rows ofmemory may be implemented in accordance with known memory architecturesor their derivatives. Briefly, a row of MA 154 includes one or moreaddressable columns of memory cells, as identified by the CAS generatedby column logic of AL 153. In an embodiment, the rows are each variouslyaddressable via the RAS generated by row logic of AL 153. A protocolused for such communication between SS 120 and pipeline 110 is supportedwith one or more state machines or other such circuitry of stages 112 a,112 b, . . . , 112 n (e.g., including the illustrative microcontrollerμC 156 of memory device 150). In some embodiments, communicationsbetween SS 120 and pipeline 110 include operations adapted from one ormore conventional techniques. By way of illustration and not limitation,μC 156 may supplement otherwise conventional command/address signalingfunctionality which, for example, conforms to some or all requirementsof a dual data rate (DDR) specification such as the DDR3 SDRAM JEDECStandard JESD79-3C, April 2008 or the like.

In an embodiment, memory device 150 further comprises circuitry IMCO 155to perform one or more in-memory compute operations based on one or moredata bits which are stored at MA 154. As described herein, IMCO 155comprises any of various types of Boolean circuit logic to receive inputsignaling based on data stored in MA 154. Such Boolean circuitry maycomprise, for example, one or more NOT gates and/or combinatorial logic(e.g., including an AND gate, OR gate, NAND gate, NOR gate, XOR gateand/or the like), in various embodiments. In-memory computing with IMCO155 is based on signaling at one or more data lines (e.g., one or morebit lines or one or more word lines) of MA 154—e.g., wherein suchsignaling includes a first signal indicating a first logic state whichis based on a first one or more stored data bits and, in someembodiments, a second signal indicating a second logic state which isbased on the first one or more stored data bits (or alternatively, basedon another one or more stored data bits). Based on such signaling,Boolean circuitry of IMCO 155 generates an output signal whichrepresents or otherwise indicates an at least partial result of acomputation using said logic state(s). In an embodiment, the one or moreBoolean operations implement an addition of two values, a multiplicationof two values, and/or any of a variety of other such operations, whichare not limiting on some embodiments. Based on the output signal, MA 154is operated—e.g., in combination with AL 153—to store one or more databits which represent a result of an in-memory computation by IMCO 155.

To facilitate the providing of data for use in, or resulting from, anin-memory computation, memory device 150 further comprises logic (suchas the illustrative configuration circuitry CFG 157 shown) which is toconfigure any of a plurality of operational modes each for variouslyaccessing array MA 154. For example, CFG 157 comprises one or moreswitches, multiplexers, demultiplexers and/or other circuitry tovariously enable or disable, selectively, one or more conductive pathsin memory device 150. In some embodiments, the plurality of modesincludes a mode to store to MA 154 data which memory device 150 hasreceived from an external agent such as SS 120 or a preceding pipelinestage. In an embodiment, the plurality of modes further comprises a modeto communicate data between array 154 and IMCO 155, and a mode tocommunicate data from array MA 154 to output interface 152.

In some embodiments, results of in-memory computations are variouslycommunicated each between a respective two of stages 112 a, 112 b, . . ., 112 n—e.g., where one in-memory computation at a given stage ofpipeline 110 is to operate on a result of another in-memory computationwhich was previously performed at an earlier stage of pipeline 110.Accordingly, pipeline 110 performs a sequence of in-memorycomputations—each at a respective one of stages 112 a, 112 b, . . . ,112 n—to generate a final result that, for example, is communicated toSS 120 via interconnect 128. In some embodiments, a last stage of thepipeline (e.g., stage 112 n) additionally or alternatively communicatesa result of at least some in-memory computation back to one or moreearlier stages of pipeline 110—e.g., as illustrated by the examplefeedback 119 shown. However, some embodiments are not limited in thisregard, and pipeline 110 may alternatively omit any such feedback 119.Feedback 119 is used, for example, to perform a next recursion of arecursive data processing with pipeline 110. Alternatively or inaddition, feedback 119 may be used to update weights values which are tobe used in operations on other input data (if any) which is subsequentlyprovided to pipeline 110 by SS 120.

FIG. 2 shows features of a method 200 to perform pipeline processing ofdata according to an embodiment. Method 200 is one example of anembodiment wherein in-memory computations are performed sequentiallyeach at a different respective stage of circuitry which includes apipeline of multiple in-series stages. Method 200 is performed withcircuitry of pipeline 110, for example.

As shown in FIG. 2, method 200 includes (at 201) storing first data at afirst memory array of a first stage of a pipeline circuit. The pipelinecircuit (including pipeline 110 and/or memory device 150, for example)comprises multiple stages arranged in an in-series configuration—e.g.,where the multiple stages comprise a first stage and a second stage. Inan embodiment, the first data is received at the pipeline circuit fromcache control circuitry or other memory controller logic coupled to thepipeline circuit. In an embodiment, the first data includes synapticweight values that, for example, variously represent neuron states of aneural network. Alternatively or in addition, the first data may includedata that is to be operated on by such a neural network—e.g., whereinthe first stage and the second stage are to implement differentrespective layers of the neural network.

Method 200 includes (at 202) performing at the first stage a firstcomputation based on the first data stored at the first memory array.The performing at 202 may include IMCO 155 (or other suitable circuitryof the first stage) receiving, or otherwise detecting, a signal from thefirst memory array which indicates a logic state based on one or morebits of the first data. Based on the logic state, circuitry such as IMCO155 performs any of a variety of computations to determine at least inpart a value (e.g., single-bit or multi-bit) which, in some embodiments,is to be stored back to the first array.

After performing the first computation at 202, method 200 (at 203)communicates a first result of the first computation from the firststage to the second stage via a first interconnect of the pipelinecircuit. The communicating at 203 is performed, for example, independentof the pipeline receiving from the memory controller any explicitcommand for such communication between the first stage and the secondstage. In one embodiment, for example, control circuitry of the firststage and/or the second stage automatically initiates such communicationin response to detecting a completion (actual or expected) of the firstcomputation. Any signal communication between the first interconnect andthe memory controller is to be via one or more stages of the multiplestages. In some embodiments, for example, the first interconnect iscoupled to the memory controller only indirectly via the one or morestages of the multiple stages. In one such embodiment, the first stageand/or the second stage is also coupled to the memory controller onlyindirectly via a respective one or more other stages of the pipeline.

In an embodiment, method 200 further comprises (at 204) storing thefirst result at a second memory array of the second stage. The secondstage provides its own in-memory computation functionality, whereby thepipeline is capable of performing multiple successive in-memorycomputations. Method 200 further comprises (at 205) performing at thesecond stage a second computation. based on the first result stored atthe second memory array, and (at 206) storing a second result of secondcomputation at the second memory array. In one example embodiment, thefirst stage and the second stage provide functionality of differentrespective layers of a neural network—e.g., wherein different stageseach provide a respective one of a convolution layer, a pooling layer, afully connected layer, or the like.

FIG. 3 shows features of a device 300 to perform in-memory computeoperations at a stage of a pipeline according to another embodiment. Inan embodiment, device 300 includes features of pipeline 110 and/ormemory device 150, for example, and/or is used to perform some or all ofmethod 200. As shown in FIG. 3, device 300 comprises input circuitry 320and output circuitry 380 to variously couple, and communicate with, amemory controller or other host logic (not shown). Input circuitry 320and output circuitry 380 may, for example, provide functionality ofinput interface 151 and output interface 152, respectively. Device 300further comprises an array 310 of memory cells which are arranged inrows and columns—e.g., wherein a given row of cells is accessible usinga corresponding word line and wherein a given column of cells isaccessible using at least one corresponding bit line.

Access logic of device 300 (e.g., providing functionality of AL 153)includes a column decoder 330 and a row decoder 340 to variously decodeaddress information of a memory access command received incommunications 322 via input circuitry 320. Communications 322 arereceived from a memory controller (or other host logic) or,alternatively, from a pipeline stage which precedes that which includesarray 310. Based on decoding of communications 322, column decoder 330and row decoder 340 variously operate word lines and bit lines to accessone or more memory cells of array 310.

In the example shown, a given column of memory cells in array 310 isaccessed using a corresponding pair of bit lines (or “line pair”)—e.g.,where said cells each have a six transistor (6T) memory cellarchitecture. For example, bit lines of array 310 include a pair of bitlines [B0, ˜B0], where the logic state of a single stored bit is able tobe communicated with bit line B0 while the opposite of that logic stateis communicated with bit line ˜B0. Similarly, an adjoining column ofmemory cells is able to be accessed with a line pair [B1, ˜B1]—e.g.,where another column of memory cells is accessed with a line pair [BN,˜BN].

The coupling of multiple cells in the same column to the same bitline—e.g., to bit line B0—enables said bit line to communicate a signalwhich represents a logical AND'ing of the respective bits stored by saidmultiple cells. Similarly, the complementary bit line—e.g., bit line˜B0—is able to concurrently communicate another signal which representsa logical AND'ing of the opposite states of said bits. For example,array 310 is shown as including a sub-array 312 accessible with wordlines Wa0, . . . , WaM, another sub-array 314 accessible with word linesWb0, . . . , WbM, and another sub-array 316 accessible with word linesWc0, . . . , WcM. This particular arrangement of subarrays 312, 314, 316is merely illustrative of one use for device 300, and is not limiting onsome embodiments.

In one such embodiment, word lines WaM, WbM (for example) are able to beconcurrently operated to access cells 313, 315 which are in respectivesub-arrays 312, 314 and also in the same column—e.g., while cell 313stores a bit A and cell 315 stores a bit B. As a result of suchoperating, a voltage level at bit line B0 indicates a logic level whichis equivalent to the AND'ed combination (A·B). By contrast, a concurrentvoltage level at bit line ˜B0 indicates a logic level which isequivalent to the AND'ed combination (!A·!B).

Device 300 includes circuitry 370—e.g., providing functionality of IMCO155—which is operable to perform one or more in-memory computeoperations based on such signaling by bit lines B0, ˜B0 (and/orsignaling by one or more additional or alternative line pairs). Forexample, circuitry 370 is coupled to bit lines of array 310 viacircuitry 360—e.g., providing functionality of CFG 157—that is operableto selectively enable, at least in part, any one of an in-memory computemode or one or other modes which support data reads from array 310and/or data writes to array 310. For example, circuitry 360 is able toselectively determine—e.g., responsive to signaling 352 from controlcircuitry μC 350 (such as microcontroller μC 156)—whether data signalsare to be directed to circuitry 370 or to an output path 362 forcommunication from device 300 via output circuitry 380. In anembodiment, circuitry 360 further provides sense amplifier and/or driverfunctionality to facilitate a communication of data to output path 362and/or a data write back to array 310 using signaling output fromcircuitry 370.

Based on signaling at one or more bit lines of array 310, circuitry 360indicates one or more corresponding logic states for use by circuitry370—e.g., for use in performing one or more in-memory computations. Aresult of such one or more in-memory computations is able to be writtenback to a cell of array 310—e.g., via circuitry 360—and, in someembodiments, is able to be subsequently communicated from memory device300 to a later pipeline stage. In one example embodiment, subarray 316is to store (e.g., at a cell 317) a result of an in-memory computationwhich is based both on a first value stored at sub-array 312, and on asecond value stored at sub-array 314. Circuitry 370 facilitates, forexample, the performance of one or more convolution calculations basedon data stored at array 310. However, any of a variety of otherin-memory computations and data writes may be performed, in differentembodiments.

In some embodiments, circuitry 360 (or other suitable configurationlogic of device 300) provides a further operational mode which is topass data through device 300—e.g., without such data being used bycircuitry 370 and wherein any storage of such data is at a memory arrayother than array 310. By way of illustration and not limitation, in someembodiments, μC 350 snoops communications 322 or otherwise performoperations which detect that input interface 320 has received (or willreceive) some data which is to be stored at a subsequent pipeline stage.In response to such detecting, μC 350 configures circuitry 360 (or othersuitable logic of device 300) to provide a pass-through interconnectpath between input interface 320 and output interface 380. Accordingly,device 300 is operable to efficiently relay data for storage at a laterpipeline stage—e.g., without requiring additional memory writeoperations, memory read operations and associated communications insupport thereof.

FIG. 4 shows features of a memory device 400 to provide a pipeline stagefor in-memory computation according to an embodiment. In an embodiment,memory device 400 provides functionality of memory device 150, of device300 or of one of pipeline stages PS 112 a, PS 112 b, . . . , PS 112n—e.g., wherein memory device 400 is to perform one or more operationsof method 200.

As shown in FIG. 4, memory device 400 comprises circuitry 430 which (forexample) provides functionality of one of IMCO 155, circuitry 370 or thelike. Switch logic of memory device 400 (e.g., including theillustrative demultiplexer DMUX 411, and multiplexer MUX 440 shown) iscoupled to selectively enable and/or disable various conductive pathsbetween circuitry 430 and a bit line 410. Similarly, one or moreconductive paths between circuitry 430 and another bit line 414 can bevariously enabled and/or disabled, selectively, with switch logic suchas MUX 440 and another demultiplexer DMUX 415.

With such switch logic, control signals 412, 416, 442 facilitate any oneof an in-memory compute mode or one or other modes which support readsfrom the memory array and/or writes to the memory array. For example, insome embodiments, a data read includes sense amplifier circuitry SA 420of memory device 400 outputting one or more data signals 422 which arebased on signaling from bit lines 410, 414—e.g., wherein a data writeincludes a driver circuitry DRV 450 outputting to one of bit lines 410,414 a signal which is based on another data signal 441 received bymemory device 400. Alternatively, driver circuitry DRV 450 (or othercircuitry of memory device 400) is operable to output a result of anin-memory computation.

During an in-memory compute mode of memory device 400, circuitry 430 isable to receive signals from bit lines 410, 414 via DMUX 411 and DMUX415 (respectively). In an embodiment, bit line 410 communicates a firstsignal representing a logic state which is based on a first one or morestored bits—e.g., wherein bit line 414 communicates a second signalrepresenting another logic state based on the first one or more storedbits (or alternatively, based on another one or more stored bits). Anin-memory operation on such states is implemented by combinatorial logicof circuitry 430 which receives the first signal and the second signal.

In the embodiment shown, bit lines 410, 414 are a pair of complementarybit lines (such as line pair B0, ˜B0, or line pair B1, ˜B2, or line pairBN, ˜BN). In one example scenario, a first memory cell storing a bit Ais coupled to each of a first word line and bit lines 410, 414.Similarly, a second memory cell storing a bit B is coupled to each of asecond word line and the bit lines 410, 414. Both the first cell and thesecond cell are able to be accessed concurrently using each of the firstword line, the second word line, and bit lines 410, 414. Such accessingresults in bit line 410 communicating a first signal which indicates afirst logic state based on bits A, B—e.g., where a voltage level of thefirst signal indicates the equivalent of a logical AND'ing of bits A, B(i.e., the function A·B). Such an AND'ing is be due at least in part tothe first memory cell and the second memory cell each being tied to bitline 410. Moreover, the accessing also results in bit line 414communicating a second signal which indicates the equivalent of alogical AND'ing of the opposite bit values (i.e., the function !A·!B).

With such signals, combinatorial logic of circuitry 430 performs anin-memory computation which (for example) adds a first stored value,which includes bit A, and a second stored value, which includes bit B.More particularly, circuitry 430 outputs a value S representing a bit ofthe arithmetic sum (A+B). In an embodiment, calculation of value S isfurther based on a carry bit C_en which, for example, is determinedbased on a calculation (not shown) of a next less significant bit ofsaid arithmetic sum. Such calculation of value S also results in thedetermining of another carry bit C_out which, for example, is availablefor use in the calculation of some next more significant bit (if any) ofsaid arithmetic sum.

FIG. 5 illustrates a sequence 500 of states 501-505 of a memory arrayduring in-memory computations performed with a pipeline circuitarchitecture according to an embodiment. In an embodiment, sequence 500is performed, for example, with one of memory device 150, 400, withdevice 300, or with one of stages PS 112 a, PS 112 b, . . . , PS 112 n.In one example embodiment, some or all of sequence 500 is based oncomputations by circuitry 370 or circuitry 430—e.g., where suchcomputations are according to method 200.

Sequence 500 illustrates one embodiment wherein computations at apipeline stage are based on data which is stored in a bit-serial format,wherein multiple bits of a given data value (e.g., including at least aportion of said data value) are stored along a single bit line of amemory array—e.g., the bits arranged in different respective word linesof the array each according to their respective bit significance. Thememory array includes memory cells arranged in columns and rows to bevariously accessed, respectively, by corresponding bit lines and wordlines (respectively). Some cells of the memory array are variouslylocated, for example, each in single column and each in a respective oneof rows Wa through W1.

In one example scenario, the column of memory cells stores, at state501, a first multi-bit value [x3-x0] equal to “0101” and a secondmulti-bit value [y3-y0] equal to “1001.” By way of illustration and notlimitation, a synaptic weight value or other state of a neural networkincludes one of [x3-x0] and [y3-y0]—e.g., wherein other data, to beprocessed by said neural network, includes the other of [x3-x0] and[y3-y0]. In such an embodiment, in-memory computations during sequence500 calculates a value [z3-z0] representing an arithmetic sum of [x3-x0]and [y3-y0]. This multi-bit value [z3-z0] is available to be furtherprocessed by additional in-memory processing at the same pipeline stageor, alternatively, to be communicated for use in other in-memoryprocessing at a subsequent pipeline stage.

In the illustrative embodiment shown, rows Wa through Wd each store adifferent respective bit of the first multi-bit value (where Wa and Wdcorrespond, respectively, to a most significant bit and a leastsignificant bit of [x3-x0]). Similarly, rows We through Wh are eachstore a different respective bit of the second multi-bit value (where Weand Wh correspond, respectively, to a most significant bit and a leastsignificant bit of [y3-y0]). At state 501, a carry bit Cout is equal to0—e.g., where state 501 is not based on any previous in-memorycalculation that might be associated with [x3-x0] and [y3-y0].

State 502 illustrates stored data (at array 310, for example) after anin-memory computation is performed—e.g., with circuitry 430—todetermine, based on bits x0, y0, a least significant bit z0 of the[z3-z0]. The bit z0 is written, for example, to a cell of the same arraycolumn which also stores [x3-x0] and [y3-y0]—e.g., where row W1 includesthe cell. In this particular example, the in-memory computation resultsin carry bit Cout being set to 1. In a similar manner, states 503, 504,505 are variously based on successive in-memory computations each todetermine, based on corresponding bits of [x3-x0] and [y3-y0], arespective next significant bit of [z3-z0]. In state 505, bits of[z3-z0] are each stored at a different respective one of rows Wi throughW1.

By building on relatively simple arithmetic operations such as thatillustrated by sequence 500—e.g., including multi-bit addition,multiplication, division, subtraction, etc.—complex in-memorycomputations are able to be performed within a given pipeline stageand/or across multiple pipeline stages to implement neural networksand/or other such functionality.

FIG. 5 also shows a sequence 520 of states 521-524 of a memory arrayduring in-memory bit-serial computations at a pipeline circuitarchitecture according to an embodiment. The bit-serial computationsillustrated by sequence 520 may include those which are illustrated bysequence 500, for example. The memory array includes memory cellsarranged in columns and rows to be variously accessed, respectively, bycorresponding bit lines and word lines (respectively). Some cells of thememory array are variously located, for example, each in a respectiveone of a columns Bs, Bt, Bu and By and each in a respective one of rowsWa through W1. At state 521, multi-bit values 530 through 533 arevariously stored, in a bit-serial format, each in a different respectiveone of columns Bs, Bt, Bu, By—e.g., wherein each of rows Wa through Wdvariously store respective bits of each of values 530 through 533.

As illustrated by state 522, values 532, 533 are copied or moved—e.g.,row-wise and column-wise—to cells in columns Bs, Bt (respectively)—e.g.,wherein each of rows We through Wh variously store respective bits ofeach of values 532, 533. Subsequently, in-memory bit-serial computationsare performed based on bits stored in column Bs to determine a value 534which, for example, represents an arithmetic sum of values 530, 532.Similarly, other in-memory bit-serial computations (based on bits storedin column Bt) are able to be performed to determine another value 535which represents an arithmetic sum of values 531, 533. In one suchembodiment, each of rows Wi through W1 variously store respective bitsof each of the values 534, 535.

This sort of data shifting and subsequent in-memory bit-serialcomputation—using data which has bit-serial (column-wise)arrangement—are able to be repeated multiple times at a given stage. Forexample, the values 534, 535 are subsequently be copied or moved—e.g.,row-wise—to other cells in columns Bs, Bt (respectively). As a result,each of rows Wa through Wd variously store respective bits of each ofvalues 534, 535 (as illustrated by state 523). As shown at state 524,value 535 then be copied or moved (row-wise and column-wise) from columnBt to cells in column Bs—e.g., where each of rows We through Wh stores adifferent respective bit of value 535. Subsequent in-memory bit-serialcomputations based on bits stored in column Bs result in the determiningof another value 536 which, for example, represents an arithmetic sum ofvalues 534, 535. In such an embodiment, rows Wi through W1 each store adifferent respective bit of value 536.

FIG. 6 shows features of a neural network 600 implemented with memorydevices arranged in a pipeline architecture according to an embodiment.Neural network 600 includes any suitable neural network such as anartificial neural network, a deep neural network, a convolutional neuralnetwork, or the like. In an embodiment, neural network 600 is providedwith functionality of pipeline 110—e.g., with a pipeline circuitarchitecture which includes one or more of memory devices 150, 400 ordevice 300.

As shown in FIG. 6, neural network 600 includes an input layer 620,hidden layers 630-633, and an output layer 640. Neural network 600 isillustrated as having three input nodes, hidden layers with four nodeseach, and six output nodes for the sake of clarity of presentation.Although some embodiments are not limited in this regard, input layer620 may include multiple nodes. For example, input layer 620 includes anumber of nodes equal to the number of elements in a feature vector fora time window multiplied by the number of feature vectors stacked forevaluation by neural network. In an embodiment, feature vectors have 23elements and 11 feature vectors are stacked such that input layer 620has 253 nodes. In other examples, feature vectors have fewer or moreelements, and fewer or more feature vectors may be stacked. For example,in some embodiments, input layer 620 alternatively has 200 to 300 nodes,300 to 400 nodes, or more nodes.

Furthermore, as in the illustrated example, neural network 600 includesfour hidden layers 630-633. However, in other examples, neural networkincludes three, five, six, or more hidden layers. Hidden layers 630-633may include any number of nodes. For example, hidden layers 630-633 mayinclude 1,500 to 2,000 nodes, 2,000 to 2,500 nodes, or the like. In anembodiment, neural network 600 includes six hidden layers each having2,048 nodes. In some examples, hidden layers 630-633 have the samenumber of nodes and in other examples, one or more layers may havedifferent numbers of nodes. Output layer 640 includes any suitablenumber of nodes such that classification scores 650 include values forcomparison and/or search to determine textual elements, recognized wordsequences, voice recognition, image recognition, gesture recognition orthe like. In one example embodiment, one or more applicable statisticalmodels include a Hidden Markov Model (HMM), where classification scores650 have a number of scores (for each time instance) equal to a numberof HMM active states or a number of available HMM states. In someexamples, output layer 640 includes a number of nodes equal to thenumber of available HMM states. For example, output layer 640 mayinclude 3,500 to 4,500 nodes, 4,500 to 5,500 nodes, or 5,500 to 6,500nodes or more. In an embodiment, output layer 640 includes 5,000 nodes.In the illustrated example, data flows from the left to the right frominput layer 620, through hidden layers 630-633, and through output layer640 as shown such that the output of input layer 620 is the input tohidden layer 630, the output of hidden layer 630 is the input to hiddenlayer 631 and so on, and such that the output of output layer 640 is theoutput of neural network 600 (e.g., classification scores 650). In someexamples, such as in the illustrated example, every node in a layer isconnected to every node in the adjacent layer (e.g., where the layersare fully connected). For example, in some embodiments, every node ofinput layer is connected to every node of hidden layer 630, every layerof hidden layer 630 is connected to every node of hidden layer 631, andso on. In other examples, some connections between nodes are not made.

As discussed, feature vectors 610 is provided to neural network 600 andneural network 600 provides classification scores 650—e.g., with outputlayer 640. Exemplary details associated with determinations made at thenodes of neural network 600 (as well as the data types used for suchdeterminations) are discussed further herein. In some examples, neuralnetwork 600 is implemented for speech recognition in a test orimplementation phase after neural network 600 has been trained in atraining phase. Such a training phase is able to determine weights fornodes of neural network 600, biases for nodes of neural network 600, andthe like.

During a training phase, weights and/or biases or the like aredetermined for neural network 600. The weights for nodes of neuralnetwork 600 are determined as any suitable number format orrepresentation, such as a 32-bit floating-point representation. However,implementing neural network 600 using such 32-bit floating-point weights(or weights having similar number representations) may becomputationally intensive and may cause problems with performance orbattery life or the like. In some embodiments, weights are converted tofixed point integer values having an associated scaling factor andcorresponding correction values are determined for some of the weights.

The figures described herein detail exemplary architectures and systemsto implement embodiments of the above. In some embodiments, one or morehardware components and/or instructions described herein are emulated asdetailed below, or implemented as software modules.

Embodiments of the instruction(s) detailed above are embodied may beembodied in a “generic vector friendly instruction format” which isdetailed herein. In other embodiments, such a format is not utilized andanother instruction format is used, however, the description herein ofthe writemask registers, various data transformations (swizzle,broadcast, etc.), addressing, etc. is generally applicable to thedescription of the embodiments of the instruction(s) above.Additionally, exemplary systems, architectures, and pipelines aredetailed herein. Embodiments of the instruction(s) above may be executedon such systems, architectures, and pipelines, but are not limited tothose detailed.

Processor cores may be implemented in different ways, for differentpurposes, and in different processors. For instance, implementations ofsuch cores may include: 1) a general purpose in-order core intended forgeneral-purpose computing; 2) a high performance general purposeout-of-order core intended for general-purpose computing; 3) a specialpurpose core intended primarily for graphics and/or scientific(throughput) computing. Implementations of different processors mayinclude: 1) a CPU including one or more general purpose in-order coresintended for general-purpose computing and/or one or more generalpurpose out-of-order cores intended for general-purpose computing; and2) a coprocessor including one or more special purpose cores intendedprimarily for graphics and/or scientific (throughput). Such differentprocessors lead to different computer system architectures, which mayinclude: 1) the coprocessor on a separate chip from the CPU; 2) thecoprocessor on a separate die in the same package as a CPU; 3) thecoprocessor on the same die as a CPU (in which case, such a coprocessoris sometimes referred to as special purpose logic, such as integratedgraphics and/or scientific (throughput) logic, or as special purposecores); and 4) a system on a chip that may include on the same die thedescribed CPU (sometimes referred to as the application core(s) orapplication processor(s)), the above described coprocessor, andadditional functionality. Exemplary core architectures are describednext, followed by descriptions of exemplary processors and computerarchitectures.

FIG. 7A is a block diagram illustrating both an exemplary in-orderpipeline and an exemplary register renaming, out-of-orderissue/execution pipeline according to embodiments of the invention. FIG.7B is a block diagram illustrating both an exemplary embodiment of anin-order architecture core and an exemplary register renaming,out-of-order issue/execution architecture core to be included in aprocessor according to embodiments of the invention. The solid linedboxes in FIGS. 7A-B illustrate the in-order pipeline and in-order core,while the optional addition of the dashed lined boxes illustrates theregister renaming, out-of-order issue/execution pipeline and core. Giventhat the in-order aspect is a subset of the out-of-order aspect, theout-of-order aspect will be described.

In FIG. 7A, a processor pipeline 700 includes a fetch stage 702, alength decode stage 704, a decode stage 706, an allocation stage 708, arenaming stage 710, a scheduling (also known as a dispatch or issue)stage 712, a register read/memory read stage 714, an execute stage 716,a write back/memory write stage 718, an exception handling stage 722,and a commit stage 724.

FIG. 7B shows processor core 790 including a front-end unit 730 coupledto an execution engine unit 750, and both are coupled to a memory unit770. The core 790 may be a reduced instruction set computing (RISC)core, a complex instruction set computing (CISC) core, a very longinstruction word (VLIW) core, or a hybrid or alternative core type. Asyet another option, the core 790 may be a special-purpose core, such as,for example, a network or communication core, compression engine,coprocessor core, general purpose computing graphics processing unit(GPGPU) core, graphics core, or the like.

The front-end unit 730 includes a branch prediction unit 732 coupled toan instruction cache unit 734, which is coupled to an instructiontranslation lookaside buffer (TLB) 736, which is coupled to aninstruction fetch unit 738, which is coupled to a decode unit 740. Thedecode unit 740 (or decoder) may decode instructions, and generate as anoutput one or more micro-operations, micro-code entry points,microinstructions, other instructions, or other control signals, whichare decoded from, or which otherwise reflect, or are derived from, theoriginal instructions. The decode unit 740 may be implemented usingvarious different mechanisms. Examples of suitable mechanisms include,but are not limited to, look-up tables, hardware implementations,programmable logic arrays (PLAs), microcode read only memories (ROMs),etc. In one embodiment, the core 790 includes a microcode ROM or othermedium that stores microcode for certain macroinstructions (e.g., indecode unit 740 or otherwise within the front-end unit 730). The decodeunit 740 is coupled to a rename/allocator unit 752 in the executionengine unit 750.

The execution engine unit 750 includes the rename/allocator unit 752coupled to a retirement unit 754 and a set of one or more schedulerunit(s) 756. The scheduler unit(s) 756 represents any number ofdifferent schedulers, including reservations stations, centralinstruction window, etc. The scheduler unit(s) 756 is coupled to thephysical register file(s) unit(s) 758. Each of the physical registerfile(s) units 758 represents one or more physical register files,different ones of which store one or more different data types, such asscalar integer, scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point, status (e.g., aninstruction pointer that is the address of the next instruction to beexecuted), etc. In one embodiment, the physical register file(s) unit758 comprises a vector registers unit, a write mask registers unit, anda scalar registers unit. These register units may provide architecturalvector registers, vector mask registers, and general-purpose registers.The physical register file(s) unit(s) 758 is overlapped by theretirement unit 754 to illustrate various ways in which registerrenaming and out-of-order execution may be implemented (e.g., using areorder buffer(s) and a retirement register file(s); using a futurefile(s), a history buffer(s), and a retirement register file(s); using aregister maps and a pool of registers; etc.). The retirement unit 754and the physical register file(s) unit(s) 758 are coupled to theexecution cluster(s) 760. The execution cluster(s) 760 includes a set ofone or more execution units 762 and a set of one or more memory accessunits 764. The execution units 762 may perform various operations (e.g.,shifts, addition, subtraction, multiplication) and on various types ofdata (e.g., scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point). While some embodimentsmay include a number of execution units dedicated to specific functionsor sets of functions, other embodiments may include only one executionunit or multiple execution units that all perform all functions. Thescheduler unit(s) 756, physical register file(s) unit(s) 758, andexecution cluster(s) 760 are shown as being possibly plural becausecertain embodiments create separate pipelines for certain types ofdata/operations (e.g., a scalar integer pipeline, a scalar floatingpoint/packed integer/packed floating point/vector integer/vectorfloating point pipeline, and/or a memory access pipeline that each havetheir own scheduler unit, physical register file(s) unit, and/orexecution cluster—and in the case of a separate memory access pipeline,certain embodiments are implemented in which only the execution clusterof this pipeline has the memory access unit(s) 764). It should also beunderstood that where separate pipelines are used, one or more of thesepipelines may be out-of-order issue/execution and the rest in-order.

The set of memory access units 764 is coupled to the memory unit 770,which includes a data TLB unit 772 coupled to a data cache unit 774coupled to a level 2 (L2) cache unit 776. In one exemplary embodiment,the memory access units 764 may include a load unit, a store addressunit, and a store data unit, each of which is coupled to the data TLBunit 772 in the memory unit 770. The instruction cache unit 734 isfurther coupled to a level 2 (L2) cache unit 776 in the memory unit 770.The L2 cache unit 776 is coupled to one or more other levels of cacheand eventually to a main memory.

By way of example, the exemplary register renaming, out-of-orderissue/execution core architecture may implement the pipeline 700 asfollows: 1) the instruction fetch 738 performs the fetch and lengthdecoding stages 702 and 704; 2) the decode unit 740 performs the decodestage 706; 3) the rename/allocator unit 752 performs the allocationstage 708 and renaming stage 710; 4) the scheduler unit(s) 756 performsthe schedule stage 712; 5) the physical register file(s) unit(s) 758 andthe memory unit 770 perform the register read/memory read stage 714; theexecution cluster 760 perform the execute stage 716; 6) the memory unit770 and the physical register file(s) unit(s) 758 perform the writeback/memory write stage 718; 7) various units may be involved in theexception handling stage 722; and 8) the retirement unit 754 and thephysical register file(s) unit(s) 758 perform the commit stage 724.

The core 790 may support one or more instructions sets (e.g., the x86instruction set (with some extensions that have been added with newerversions); the MIPS instruction set of MIPS Technologies of Sunnyvale,Calif.; the ARM instruction set (with optional additional extensionssuch as NEON) of ARM Holdings of Sunnyvale, Calif.), including theinstruction(s) described herein. In one embodiment, the core 790includes logic to support a packed data instruction set extension (e.g.,AVX1, AVX2), thereby allowing the operations used by many multimediaapplications to be performed using packed data.

It should be understood that the core may support multithreading(executing two or more parallel sets of operations or threads), and maydo so in a variety of ways including time sliced multithreading,simultaneous multithreading (where a single physical core provides alogical core for each of the threads that physical core issimultaneously multithreading), or a combination thereof (e.g., timesliced fetching and decoding and simultaneous multithreading thereaftersuch as in the Intel® Hyperthreading technology).

While register renaming is described in the context of out-of-orderexecution, it should be understood that register renaming may be used inan in-order architecture. While the illustrated embodiment of theprocessor also includes separate instruction and data cache units734/774 and a shared L2 cache unit 776, alternative embodiments may havea single internal cache for both instructions and data, such as, forexample, a Level 1 (L) internal cache, or multiple levels of internalcache. In some embodiments, the system may include a combination of aninternal cache and an external cache that is external to the core and/orthe processor. Alternatively, all of the cache may be external to thecore and/or the processor.

FIG. 8 is a block diagram of a processor 800 that may have more than onecore, may have an integrated memory controller, and may have integratedgraphics according to embodiments of the invention. The solid linedboxes in FIG. 8 illustrate a processor 800 with a single core 802A, asystem agent 810, a set of one or more bus controller units 816, whilethe optional addition of the dashed lined boxes illustrates analternative processor 800 with multiple cores 802A-N, a set of one ormore integrated memory controller unit(s) 814 in the system agent unit810, and special purpose logic 808.

Thus, different implementations of the processor 800 may include: 1) aCPU with the special purpose logic 808 being integrated graphics and/orscientific (throughput) logic (which may include one or more cores), andthe cores 802A-N being one or more general purpose cores (e.g., generalpurpose in-order cores, general purpose out-of-order cores, acombination of the two); 2) a coprocessor with the cores 802A-N being alarge number of special purpose cores intended primarily for graphicsand/or scientific (throughput); and 3) a coprocessor with the cores802A-N being a large number of general purpose in-order cores. Thus, theprocessor 800 may be a general-purpose processor, coprocessor orspecial-purpose processor, such as, for example, a network orcommunication processor, compression engine, graphics processor, GPGPU(general purpose graphics processing unit), a high-throughput manyintegrated core (MIC) coprocessor (including 30 or more cores), embeddedprocessor, or the like. The processor may be implemented on one or morechips. The processor 800 may be a part of and/or may be implemented onone or more substrates using any of a number of process technologies,such as, for example, BiCMOS, CMOS, or NMOS.

The memory hierarchy includes one or more levels of cache within thecores (e.g., including cache units 804A-N), a set or one or more sharedcache units 806, and external memory (not shown) coupled to the set ofintegrated memory controller units 814. The set of shared cache units806 may include one or more mid-level caches, such as level 2 (L2),level 3 (L3), level 4 (L4), or other levels of cache, a last level cache(LLC), and/or combinations thereof. While in one embodiment a ring-basedinterconnect unit 812 interconnects the integrated graphics logic 808,the set of shared cache units 806, and the system agent unit810/integrated memory controller unit(s) 814, alternative embodimentsmay use any number of well-known techniques for interconnecting suchunits. In one embodiment, coherency is maintained between one or morecache units 806 and cores 802A-N.

In some embodiments, one or more of the cores 802A-N are capable ofmultithreading. The system agent 810 includes those componentscoordinating and operating cores 802A-N. The system agent unit 810 mayinclude for example a power control unit (PCU) and a display unit. ThePCU may be or include logic and components needed for regulating thepower state of the cores 802A-N and the integrated graphics logic 808.The display unit is for driving one or more externally connecteddisplays.

The cores 802A-N may be homogenous or heterogeneous in terms ofarchitecture instruction set; that is, two or more of the cores 802A-Nmay be capable of execution the same instruction set, while others maybe capable of executing only a subset of that instruction set or adifferent instruction set.

FIGS. 9-11 are block diagrams of exemplary computer architectures. Othersystem designs and configurations known in the arts for laptops,desktops, handheld PCs, personal digital assistants, engineeringworkstations, servers, network devices, network hubs, switches, embeddedprocessors, digital signal processors (DSPs), graphics devices, videogame devices, set-top boxes, micro controllers, cell phones, portablemedia players, hand held devices, and various other electronic devices,are also suitable. In general, a huge variety of systems or electronicdevices capable of incorporating a processor and/or other executionlogic as disclosed herein are generally suitable.

Referring now to FIG. 9, shown is a block diagram of a system 900 inaccordance with one embodiment of the present invention. The system 900may include one or more processors 910, 915, which are coupled to acontroller hub 920. In one embodiment the controller hub 920 includes agraphics memory controller hub (GMCH) 990 and an Input/Output Hub (IOH)950 (which may be on separate chips); the GMCH 990 includes memory andgraphics controllers to which are coupled memory 940 and a coprocessor945; the IOH 950 is couples input/output (I/O) devices 960 to the GMCH990. Alternatively, one or both of the memory and graphics controllersare integrated within the processor (as described herein), the memory940 and the coprocessor 945 are coupled directly to the processor 910,and the controller hub 920 in a single chip with the IOH 950.

The optional nature of additional processors 915 is denoted in FIG. 9with broken lines. Each processor 910, 915 may include one or more ofthe processing cores described herein and may be some version of theprocessor 800.

The memory 940 may be, for example, dynamic random access memory (DRAM),phase change memory (PCM), or a combination of the two. For at least oneembodiment, the controller hub 920 communicates with the processor(s)910, 915 via a multi-drop bus, such as a frontside bus (FSB),point-to-point interface such as QuickPath Interconnect (QPI), orsimilar connection 995.

In one embodiment, the coprocessor 945 is a special-purpose processor,such as, for example, a high-throughput MIC processor, a network orcommunication processor, compression engine, graphics processor, GPGPU,embedded processor, or the like. In one embodiment, controller hub 920may include an integrated graphics accelerator.

There can be a variety of differences between the physical resources910, 915 in terms of a spectrum of metrics of merit includingarchitectural, microarchitectural, thermal, power consumptioncharacteristics, and the like.

In one embodiment, the processor 910 executes instructions that controldata processing operations of a general type. Embedded within theinstructions may be coprocessor instructions. The processor 910recognizes these coprocessor instructions as being of a type that shouldbe executed by the attached coprocessor 945. Accordingly, the processor910 issues these coprocessor instructions (or control signalsrepresenting coprocessor instructions) on a coprocessor bus or otherinterconnect, to coprocessor 945. Coprocessor(s) 945 accept and executethe received coprocessor instructions.

Referring now to FIG. 10, shown is a block diagram of a first morespecific exemplary system 1000 in accordance with an embodiment of thepresent invention. As shown in FIG. 10, multiprocessor system 1000 is apoint-to-point interconnect system, and includes a first processor 1070and a second processor 1080 coupled via a point-to-point interconnect1050. Each of processors 1070 and 1080 may be some version of theprocessor 800. In one embodiment of the invention, processors 1070 and1080 are respectively processors 910 and 915, while coprocessor 1038 iscoprocessor 945. In another embodiment, processors 1070 and 1080 arerespectively processor 910 coprocessor 945.

Processors 1070 and 1080 are shown including integrated memorycontroller (IMC) units 1072 and 1082, respectively. Processor 1070 alsoincludes as part of its bus controller units point-to-point (P-P)interfaces 1076 and 1078; similarly, second processor 1080 includes P-Pinterfaces 1086 and 1088. Processors 1070, 1080 may exchange informationvia a point-to-point (P-P) interface 1050 using P-P interface circuits1078, 1088. As shown in FIG. 10, IMCs 1072 and 1082 couple theprocessors to respective memories, namely a memory 1032 and a memory1034, which may be portions of main memory locally attached to therespective processors.

Processors 1070, 1080 may each exchange information with a chipset 1090via individual P-P interfaces 1052, 1054 using point to point interfacecircuits 1076, 1094, 1086, 1098. Chipset 1090 may optionally exchangeinformation with the coprocessor 1038 via a high-performance interface1092 and an interconnect 1039. In one embodiment, the coprocessor 1038is a special-purpose processor, such as, for example, a high-throughputMIC processor, a network or communication processor, compression engine,graphics processor, GPGPU, embedded processor, or the like.

A shared cache (not shown) may be included in either processor oroutside of both processors, yet connected with the processors via P-Pinterconnect, such that either or both processors' local cacheinformation may be stored in the shared cache if a processor is placedinto a low power mode.

Chipset 1090 may be coupled to a first bus 1016 via an interface 1096.In one embodiment, first bus 1016 may be a Peripheral ComponentInterconnect (PCI) bus, or a bus such as a PCI Express bus or anotherthird generation I/O interconnect bus, although the scope of the presentinvention is not so limited.

As shown in FIG. 10, various I/O devices 1014 may be coupled to firstbus 1016, along with a bus bridge 1018 which couples first bus 1016 to asecond bus 1020. In one embodiment, one or more additional processor(s)1015, such as coprocessors, high-throughput MIC processors, GPGPU's,accelerators (such as, e.g., graphics accelerators or digital signalprocessing (DSP) units), field programmable gate arrays, or any otherprocessor, are coupled to first bus 1016. In one embodiment, second bus1020 may be a low pin count (LPC) bus. Various devices may be coupled toa second bus 1020 including, for example, a keyboard and/or mouse 1022,communication devices 1027 and a storage unit 1028 such as a disk driveor other mass storage device which may include instructions/code anddata 1030, in one embodiment. Further, an audio I/O 1024 may be coupledto the second bus 1020. Note that other architectures are possible. Forexample, instead of the point-to-point architecture of FIG. 10, a systemmay implement a multi-drop bus or other such architecture.

Referring now to FIG. 11, shown is a block diagram of a SoC 1100 inaccordance with an embodiment of the present invention. Similar elementsin FIG. 8 bear like reference numerals. Also, dashed lined boxes areoptional features on more advanced SoCs. In FIG. 11, an interconnectunit(s) 1102 is coupled to: an application processor 1110 which includesa set of one or more cores 802A-N and shared cache unit(s) 806; a systemagent unit 810; a bus controller unit(s) 816; an integrated memorycontroller unit(s) 814; a set or one or more coprocessors 1120 which mayinclude integrated graphics logic, an image processor, an audioprocessor, and a video processor; an static random access memory (SRAM)unit 1130; a direct memory access (DMA) unit 1132; and a display unit1140 for coupling to one or more external displays. In one embodiment,the coprocessor(s) 1120 include a special-purpose processor, such as,for example, a network or communication processor, compression engine,GPGPU, a high-throughput MIC processor, embedded processor, or the like.

Embodiments of the mechanisms disclosed herein may be implemented inhardware, software, firmware, or a combination of such implementationapproaches. Embodiments of the invention may be implemented as computerprograms or program code executing on programmable systems comprising atleast one processor, a storage system (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device.

Program code, such as code 1030 illustrated in FIG. 10, may be appliedto input instructions to perform the functions described herein andgenerate output information. The output information may be applied toone or more output devices, in known fashion. For purposes of thisapplication, a processing system includes any system that has aprocessor, such as, for example; a digital signal processor (DSP), amicrocontroller, an application specific integrated circuit (ASIC), or amicroprocessor.

The program code may be implemented in a high level procedural orobject-oriented programming language to communicate with a processingsystem. The program code may also be implemented in assembly or machinelanguage, if desired. In fact, the mechanisms described herein are notlimited in scope to any particular programming language. In any case,the language may be a compiled or interpreted language.

One or more aspects of at least one embodiment may be implemented byrepresentative instructions stored on a machine-readable medium whichrepresents various logic within the processor, which when read by amachine causes the machine to fabricate logic to perform the techniquesdescribed herein. Such representations, known as “IP cores” may bestored on a tangible, machine readable medium and supplied to variouscustomers or manufacturing facilities to load into the fabricationmachines that actually make the logic or processor.

Such machine-readable storage media may include, without limitation,non-transitory, tangible arrangements of articles manufactured or formedby a machine or device, including storage media such as hard disks, anyother type of disk including floppy disks, optical disks, compact diskread-only memories (CD-ROMs), compact disk rewritable's (CD-RWs), andmagneto-optical disks, semiconductor devices such as read-only memories(ROMs), random access memories (RAMs) such as dynamic random accessmemories (DRAMs), static random access memories (SRAMs), erasableprogrammable read-only memories (EPROMs), flash memories, electricallyerasable programmable read-only memories (EEPROMs), phase change memory(PCM), magnetic or optical cards, or any other type of media suitablefor storing electronic instructions.

Accordingly, embodiments of the invention also include non-transitory,tangible machine-readable media containing instructions or containingdesign data, such as Hardware Description Language (HDL), which definesstructures, circuits, apparatuses, processors and/or system featuresdescribed herein. Such embodiments may also be referred to as programproducts.

Techniques and architectures for performing in-memory computations aredescribed herein. In the above description, for purposes of explanation,numerous specific details are set forth in order to provide a thoroughunderstanding of certain embodiments. It will be apparent, however, toone skilled in the art that certain embodiments can be practiced withoutthese specific details. In other instances, structures and devices areshown in block diagram form in order to avoid obscuring the description.

Reference in the specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the invention. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

Some portions of the detailed description herein are presented in termsof algorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the computingarts to most effectively convey the substance of their work to othersskilled in the art. An algorithm is here, and generally, conceived to bea self-consistent sequence of steps leading to a desired result. Thesteps are those requiring physical manipulations of physical quantities.Usually, though not necessarily, these quantities take the form ofelectrical or magnetic signals capable of being stored, transferred,combined, compared, and otherwise manipulated. It has proven convenientat times, principally for reasons of common usage, to refer to thesesignals as bits, values, elements, symbols, characters, terms, numbers,or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the discussion herein, itis appreciated that throughout the description, discussions utilizingterms such as “processing” or “computing” or “calculating” or“determining” or “displaying” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that manipulates and transforms data represented as physical(electronic) quantities within the computer system's registers andmemories into other data similarly represented as physical quantitieswithin the computer system memories or registers or other suchinformation storage, transmission or display devices.

Certain embodiments also relate to apparatus for performing theoperations herein. This apparatus may be specially constructed for therequired purposes, or it may comprise a general purpose computerselectively activated or reconfigured by a computer program stored inthe computer. Such a computer program may be stored in a computerreadable storage medium, such as, but is not limited to, any type ofdisk including floppy disks, optical disks, CD-ROMs, andmagnetic-optical disks, read-only memories (ROMs), random accessmemories (RAMs) such as dynamic RAM (DRAM), EPROMs, EEPROMs, magnetic oroptical cards, or any type of media suitable for storing electronicinstructions, and coupled to a computer system bus.

The algorithms and displays presented herein are not inherently relatedto any particular computer or other apparatus. Various general purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear from the description herein.In addition, certain embodiments are not described with reference to anyparticular programming language. It will be appreciated that a varietyof programming languages may be used to implement the teachings of suchembodiments as described herein.

Besides what is described herein, various modifications may be made tothe disclosed embodiments and implementations thereof without departingfrom their scope. Therefore, the illustrations and examples hereinshould be construed in an illustrative, and not a restrictive sense. Thescope of the invention should be measured solely by reference to theclaims that follow.

What is claimed is:
 1. A pipeline circuit for performing an in-memorycomputation, the pipeline circuit comprising: a first stage of multiplestages of the pipeline circuit, the multiple stages arranged in anin-series configuration, the first stage comprising: a first interfaceto receive first data from a controller circuit coupled to the pipelinecircuit; a first memory array to store the first data; and firstcircuitry coupled to the first memory array, the first circuitry toperform a first computation based on the first data; an interconnectcoupled to receive a first result of the first computation from thefirst stage, wherein any communication between the interconnect and thecontroller circuit is to be via one or more of the multiple stages; asecond stage of the multiple stages, the second stage comprising: asecond interface to receive the first result from the interconnect; asecond memory array to store the first result; and second circuitry toperform a second computation based on the first result stored at thesecond memory array.
 2. The pipeline circuit of claim 1, wherein thefirst circuitry to perform the first computation comprises the firstcircuitry to automatically perform multiple accesses to the first memoryarray according to a sequence which is predefined at the first stage. 3.The pipeline circuit of claim 1, wherein the first stage and the secondstage are to automatically communicate the first result independent ofany explicit command from the controller circuit to communicate thefirst result.
 4. The pipeline circuit of claim 1, wherein the secondstage is further to: receive second data from the first stage; and passthe second data through to a respective subsequent stage of the pipelinecircuit, wherein any storage of the second data at a memory array isexternal to the second stage.
 5. The pipeline circuit of claim 1,wherein the first stage is further to: receive a feedback from arespective subsequent stage of the multiple stages; and perform, basedon the feedback, a next recursion of a recursive data processing withthe pipeline circuit.
 6. The pipeline circuit of claim 1, wherein thepipeline circuit is to receive the first data via another interconnectwhich is coupled between the pipeline circuit and the controllercircuit, wherein a portion of the other interconnect is further coupledbetween the controller circuit and a cache memory.
 7. The pipelinecircuit of claim 6, wherein a processor comprises the cache memory andthe pipeline circuit.
 8. The pipeline circuit of claim 7, wherein a coreof the processor comprises the cache memory.
 9. The pipeline circuit ofclaim 1, wherein a multi-core processor comprises the pipeline circuit.10. The pipeline circuit of claim 1, wherein the first memory array andthe second memory array comprise static random access memory cells. 11.The pipeline circuit of claim 1, wherein the first circuitry to performthe first computation or the second circuitry to perform the secondcomputation comprises one of the first circuitry or the second circuitryto perform a bit-serial computation.
 12. A processor for performing anin-memory computation, the processor comprising: a processor corecomprising a controller circuit; a pipeline circuit coupled thecontroller circuit, the pipeline circuit comprising: a first stage ofmultiple stages of the pipeline circuit, the multiple stages arranged inan in-series configuration, the first stage comprising: a first memoryarray to store first data provided by the controller circuit; and firstcircuitry coupled to perform a first in-memory computation based on thefirst data; an interconnect coupled to receive a result of the firstin-memory computation from the first stage, wherein any communicationbetween the interconnect and the controller circuit is to be via one ormore of the multiple stages; a second stage of the multiple stages, thesecond stage comprising: a second memory array to receive and store theresult; and second circuitry coupled to access the second memory array,and to perform a second in-memory computation based on the result. 13.The processor of claim 12, wherein the first circuitry to perform thefirst in-memory computation comprises the first circuitry toautomatically perform multiple accesses to the first memory arrayaccording to a sequence which is predefined at the first stage.
 14. Theprocessor of claim 12, further comprising a cache memory, wherein thepipeline circuit is to receive the first data via another interconnectwhich is coupled between the pipeline circuit and the controllercircuit, wherein a portion of the other interconnect is further coupledbetween the controller circuit and a cache memory.
 15. The processor ofclaim 12, further comprising one or more other processor cores, whereinthe pipeline circuit is further coupled to received respective data fromeach of the one or more other processor cores.
 16. A method at apipeline circuit for performing in-memory computations, the methodcomprising: receiving first data from a controller circuit coupled tothe pipeline circuit, wherein the pipeline circuit comprises multiplestages arranged in an in-series configuration, the multiple stagescomprising a first stage and a second stage; storing the first data at afirst memory array of the first stage; performing at the first stage afirst computation based on the first data stored at the first memoryarray; communicating a first result of the first computation from thefirst stage to the second stage via a first interconnect of the pipelinecircuit, wherein any signal communication between the first interconnectand the controller circuit is to be via one or more stages of themultiple stages; storing the first result at a second memory array ofthe second stage; performing at the second stage a second computationbased on the first result stored at the second memory array; and storinga second result of second computation at the second memory array. 17.The method of claim 16, wherein performing the first computationcomprises automatically performing multiple accesses to the first memoryarray according to a sequence which is predefined at the first stage.18. The method of claim 16, wherein communicating the first resultcomprises automatically communicating with the first stage and thesecond stage independent of any explicit command from the controllercircuit to communicate the first result.
 19. The method of claim 16,further comprising: at the first stage, receiving a feedback from arespective subsequent stage of the multiple stages; and based on thefeedback, performing a next recursion of a recursive data processingwith the pipeline circuit.
 20. A system comprising a pipeline circuitfor performing an in-memory computation, the pipeline circuitcomprising: a first stage of multiple stages of the pipeline circuit,the multiple stages arranged in an in-series configuration, the firststage comprising: a first interface to receive first data from acontroller circuit coupled to the pipeline circuit; a first memory arrayto store the first data; and first circuitry coupled to the first memoryarray, the first circuitry to perform a first computation based on thefirst data; an interconnect coupled to receive a first result of thefirst computation from the first stage, wherein any communicationbetween the interconnect and the controller circuit is to be via one ormore of the multiple stages; a second stage of the multiple stages, thesecond stage comprising: a second interface to receive the first resultfrom the interconnect; a second memory array to store the first result;and second circuitry to perform a second computation based on the firstresult stored at the second memory array; and a display device coupledto the pipeline circuit, the display device to display an image based ona signal communicated with the pipeline circuit, the signal based on thesecond computation.
 21. The system of claim 20, wherein the firstcircuitry to perform the first computation comprises the first circuitryto automatically perform multiple accesses to the first memory arrayaccording to a sequence which is predefined at the first stage.
 22. Thesystem of claim 20, wherein the first stage and the second stage are toautomatically communicate the first result independent of any explicitcommand from the controller circuit to communicate the first result. 23.The system of claim 20, wherein the second stage is further to: receivesecond data from the first stage; and pass the second data through to arespective subsequent stage of the pipeline circuit, wherein any storageof the second data at a memory array is external to the second stage.